Overview

Dataset statistics

Number of variables38
Number of observations1000
Missing cells21780
Missing cells (%)57.3%
Total size in memory3.3 MiB
Average record size in memory3.4 KiB

Variable types

Numeric1
Text18
Unsupported18
URL1

Alerts

type_of_notice_description has constant value ""Constant
section_name has constant value ""Constant
special_case_reason_description has 874 (87.4%) missing valuesMissing
pin has 35 (3.5%) missing valuesMissing
address_to_request has 398 (39.8%) missing valuesMissing
contact_name has 353 (35.3%) missing valuesMissing
contact_phone has 385 (38.5%) missing valuesMissing
email has 346 (34.6%) missing valuesMissing
contract_amount has 1000 (100.0%) missing valuesMissing
contact_fax has 1000 (100.0%) missing valuesMissing
additional_description_1 has 22 (2.2%) missing valuesMissing
additional_description_2 has 1000 (100.0%) missing valuesMissing
additional_description_3 has 1000 (100.0%) missing valuesMissing
other_info_1 has 561 (56.1%) missing valuesMissing
other_info_2 has 1000 (100.0%) missing valuesMissing
other_info_3 has 1000 (100.0%) missing valuesMissing
vendor_name has 1000 (100.0%) missing valuesMissing
vendor_address has 1000 (100.0%) missing valuesMissing
printout_1 has 1000 (100.0%) missing valuesMissing
printout_2 has 1000 (100.0%) missing valuesMissing
printout_3 has 1000 (100.0%) missing valuesMissing
document_links has 806 (80.6%) missing valuesMissing
event_date has 1000 (100.0%) missing valuesMissing
building_name has 1000 (100.0%) missing valuesMissing
street_address_1 has 1000 (100.0%) missing valuesMissing
street_address_2 has 1000 (100.0%) missing valuesMissing
city has 1000 (100.0%) missing valuesMissing
state has 1000 (100.0%) missing valuesMissing
zip_code has 1000 (100.0%) missing valuesMissing
0 has unique valuesUnique
request_id has unique valuesUnique
contract_amount is an unsupported type, check if it needs cleaning or further analysisUnsupported
contact_fax is an unsupported type, check if it needs cleaning or further analysisUnsupported
additional_description_2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
additional_description_3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
other_info_2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
other_info_3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
vendor_name is an unsupported type, check if it needs cleaning or further analysisUnsupported
vendor_address is an unsupported type, check if it needs cleaning or further analysisUnsupported
printout_1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
printout_2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
printout_3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
event_date is an unsupported type, check if it needs cleaning or further analysisUnsupported
building_name is an unsupported type, check if it needs cleaning or further analysisUnsupported
street_address_1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
street_address_2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
city is an unsupported type, check if it needs cleaning or further analysisUnsupported
state is an unsupported type, check if it needs cleaning or further analysisUnsupported
zip_code is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-09 21:25:49.793387
Analysis finished2023-12-09 21:25:51.357450
Duration1.56 second
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

0
Real number (ℝ)

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean500.5
Minimum1
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-09T21:25:51.470291image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile50.95
Q1250.75
median500.5
Q3750.25
95-th percentile950.05
Maximum1000
Range999
Interquartile range (IQR)499.5

Descriptive statistics

Standard deviation288.8194361
Coefficient of variation (CV)0.5770618104
Kurtosis-1.2
Mean500.5
Median Absolute Deviation (MAD)250
Skewness0
Sum500500
Variance83416.66667
MonotonicityStrictly increasing
2023-12-09T21:25:51.634137image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
672 1
 
0.1%
659 1
 
0.1%
660 1
 
0.1%
661 1
 
0.1%
662 1
 
0.1%
663 1
 
0.1%
664 1
 
0.1%
665 1
 
0.1%
666 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
ValueCountFrequency (%)
1000 1
0.1%
999 1
0.1%
998 1
0.1%
997 1
0.1%
996 1
0.1%

request_id
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size66.5 KiB
2023-12-09T21:25:51.979707image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters11000
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st row20231109109
2nd row20231109111
3rd row20231108102
4th row20231003115
5th row20231023117
ValueCountFrequency (%)
20230822113 1
 
0.1%
20230404122 1
 
0.1%
20220315102 1
 
0.1%
20230329112 1
 
0.1%
20230518117 1
 
0.1%
20231101101 1
 
0.1%
20230419122 1
 
0.1%
20230302120 1
 
0.1%
20230503116 1
 
0.1%
20230710106 1
 
0.1%
Other values (990) 990
99.0%
2023-12-09T21:25:52.442010image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2889
26.3%
0 2729
24.8%
1 2326
21.1%
3 1401
12.7%
4 333
 
3.0%
5 302
 
2.7%
8 296
 
2.7%
9 245
 
2.2%
7 241
 
2.2%
6 238
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2889
26.3%
0 2729
24.8%
1 2326
21.1%
3 1401
12.7%
4 333
 
3.0%
5 302
 
2.7%
8 296
 
2.7%
9 245
 
2.2%
7 241
 
2.2%
6 238
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 11000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2889
26.3%
0 2729
24.8%
1 2326
21.1%
3 1401
12.7%
4 333
 
3.0%
5 302
 
2.7%
8 296
 
2.7%
9 245
 
2.2%
7 241
 
2.2%
6 238
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2889
26.3%
0 2729
24.8%
1 2326
21.1%
3 1401
12.7%
4 333
 
3.0%
5 302
 
2.7%
8 296
 
2.7%
9 245
 
2.2%
7 241
 
2.2%
6 238
 
2.2%
Distinct213
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
2023-12-09T21:25:52.775775image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters23000
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)1.9%

Sample

1st row2023-11-17T00:00:00.000
2nd row2023-11-17T00:00:00.000
3rd row2023-11-17T00:00:00.000
4th row2023-11-16T00:00:00.000
5th row2023-11-16T00:00:00.000
ValueCountFrequency (%)
2023-05-31t00:00:00.000 19
 
1.9%
2023-03-27t00:00:00.000 13
 
1.3%
2023-11-13t00:00:00.000 12
 
1.2%
2023-11-09t00:00:00.000 11
 
1.1%
2023-09-11t00:00:00.000 10
 
1.0%
2023-10-27t00:00:00.000 10
 
1.0%
2023-01-27t00:00:00.000 10
 
1.0%
2023-04-27t00:00:00.000 10
 
1.0%
2023-09-13t00:00:00.000 10
 
1.0%
2023-09-05t00:00:00.000 10
 
1.0%
Other values (203) 885
88.5%
2023-12-09T21:25:53.223930image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11305
49.2%
2 2454
 
10.7%
- 2000
 
8.7%
: 2000
 
8.7%
3 1284
 
5.6%
T 1000
 
4.3%
. 1000
 
4.3%
1 794
 
3.5%
5 226
 
1.0%
7 218
 
0.9%
Other values (4) 719
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17000
73.9%
Other Punctuation 3000
 
13.0%
Dash Punctuation 2000
 
8.7%
Uppercase Letter 1000
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11305
66.5%
2 2454
 
14.4%
3 1284
 
7.6%
1 794
 
4.7%
5 226
 
1.3%
7 218
 
1.3%
6 195
 
1.1%
9 183
 
1.1%
4 178
 
1.0%
8 163
 
1.0%
Other Punctuation
ValueCountFrequency (%)
: 2000
66.7%
. 1000
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2000
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22000
95.7%
Latin 1000
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11305
51.4%
2 2454
 
11.2%
- 2000
 
9.1%
: 2000
 
9.1%
3 1284
 
5.8%
. 1000
 
4.5%
1 794
 
3.6%
5 226
 
1.0%
7 218
 
1.0%
6 195
 
0.9%
Other values (3) 524
 
2.4%
Latin
ValueCountFrequency (%)
T 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11305
49.2%
2 2454
 
10.7%
- 2000
 
8.7%
: 2000
 
8.7%
3 1284
 
5.6%
T 1000
 
4.3%
. 1000
 
4.3%
1 794
 
3.5%
5 226
 
1.0%
7 218
 
0.9%
Other values (4) 719
 
3.1%
Distinct215
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
2023-12-09T21:25:53.531244image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters23000
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)1.8%

Sample

1st row2023-11-17T00:00:00.000
2nd row2023-11-17T00:00:00.000
3rd row2023-11-17T00:00:00.000
4th row2023-11-16T00:00:00.000
5th row2023-11-16T00:00:00.000
ValueCountFrequency (%)
2023-05-31t00:00:00.000 20
 
2.0%
2023-11-13t00:00:00.000 14
 
1.4%
2023-03-27t00:00:00.000 11
 
1.1%
2023-09-11t00:00:00.000 10
 
1.0%
2023-02-21t00:00:00.000 10
 
1.0%
2023-11-09t00:00:00.000 10
 
1.0%
2023-09-13t00:00:00.000 10
 
1.0%
2023-09-05t00:00:00.000 10
 
1.0%
2023-03-20t00:00:00.000 9
 
0.9%
2023-05-30t00:00:00.000 9
 
0.9%
Other values (205) 887
88.7%
2023-12-09T21:25:53.953610image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11305
49.2%
2 2458
 
10.7%
- 2000
 
8.7%
: 2000
 
8.7%
3 1295
 
5.6%
T 1000
 
4.3%
. 1000
 
4.3%
1 800
 
3.5%
5 229
 
1.0%
7 209
 
0.9%
Other values (4) 704
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17000
73.9%
Other Punctuation 3000
 
13.0%
Dash Punctuation 2000
 
8.7%
Uppercase Letter 1000
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11305
66.5%
2 2458
 
14.5%
3 1295
 
7.6%
1 800
 
4.7%
5 229
 
1.3%
7 209
 
1.2%
6 192
 
1.1%
9 182
 
1.1%
4 171
 
1.0%
8 159
 
0.9%
Other Punctuation
ValueCountFrequency (%)
: 2000
66.7%
. 1000
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2000
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22000
95.7%
Latin 1000
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11305
51.4%
2 2458
 
11.2%
- 2000
 
9.1%
: 2000
 
9.1%
3 1295
 
5.9%
. 1000
 
4.5%
1 800
 
3.6%
5 229
 
1.0%
7 209
 
0.9%
6 192
 
0.9%
Other values (3) 512
 
2.3%
Latin
ValueCountFrequency (%)
T 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11305
49.2%
2 2458
 
10.7%
- 2000
 
8.7%
: 2000
 
8.7%
3 1295
 
5.6%
T 1000
 
4.3%
. 1000
 
4.3%
1 800
 
3.5%
5 229
 
1.0%
7 209
 
0.9%
Other values (4) 704
 
3.1%
Distinct42
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size79.0 KiB
2023-12-09T21:25:54.260068image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length51
Median length38
Mean length23.726
Min length7

Characters and Unicode

Total characters23726
Distinct characters49
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)0.8%

Sample

1st rowHousing Authority
2nd rowEducation
3rd rowEconomic Development Corporation
4th rowAdministration for Children's Services
5th rowParks and Recreation
ValueCountFrequency (%)
authority 231
 
8.5%
and 190
 
7.0%
services 187
 
6.9%
citywide 168
 
6.2%
administrative 168
 
6.2%
housing 164
 
6.0%
construction 144
 
5.3%
environmental 135
 
5.0%
protection 135
 
5.0%
parks 103
 
3.8%
Other values (82) 1089
40.1%
2023-12-09T21:25:54.937407image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 2408
 
10.1%
t 2247
 
9.5%
n 1942
 
8.2%
o 1936
 
8.2%
e 1754
 
7.4%
1714
 
7.2%
r 1596
 
6.7%
s 1107
 
4.7%
a 1080
 
4.6%
c 811
 
3.4%
Other values (39) 7131
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19364
81.6%
Uppercase Letter 2541
 
10.7%
Space Separator 1714
 
7.2%
Math Symbol 59
 
0.2%
Other Punctuation 27
 
0.1%
Dash Punctuation 21
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 2408
12.4%
t 2247
11.6%
n 1942
10.0%
o 1936
10.0%
e 1754
9.1%
r 1596
8.2%
s 1107
 
5.7%
a 1080
 
5.6%
c 811
 
4.2%
u 627
 
3.2%
Other values (13) 3856
19.9%
Uppercase Letter
ValueCountFrequency (%)
C 457
18.0%
A 423
16.6%
H 304
12.0%
S 280
11.0%
P 279
11.0%
E 205
8.1%
D 154
 
6.1%
R 114
 
4.5%
Y 81
 
3.2%
N 79
 
3.1%
Other values (10) 165
 
6.5%
Other Punctuation
ValueCountFrequency (%)
' 14
51.9%
. 10
37.0%
/ 3
 
11.1%
Space Separator
ValueCountFrequency (%)
1714
100.0%
Math Symbol
ValueCountFrequency (%)
+ 59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21905
92.3%
Common 1821
 
7.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 2408
 
11.0%
t 2247
 
10.3%
n 1942
 
8.9%
o 1936
 
8.8%
e 1754
 
8.0%
r 1596
 
7.3%
s 1107
 
5.1%
a 1080
 
4.9%
c 811
 
3.7%
u 627
 
2.9%
Other values (33) 6397
29.2%
Common
ValueCountFrequency (%)
1714
94.1%
+ 59
 
3.2%
- 21
 
1.2%
' 14
 
0.8%
. 10
 
0.5%
/ 3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23726
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 2408
 
10.1%
t 2247
 
9.5%
n 1942
 
8.2%
o 1936
 
8.2%
e 1754
 
7.4%
1714
 
7.2%
r 1596
 
6.7%
s 1107
 
4.7%
a 1080
 
4.6%
c 811
 
3.4%
Other values (39) 7131
30.1%
Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
2023-12-09T21:25:55.109601image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12000
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSolicitation
2nd rowSolicitation
3rd rowSolicitation
4th rowSolicitation
5th rowSolicitation
ValueCountFrequency (%)
solicitation 1000
100.0%
2023-12-09T21:25:55.380825image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 3000
25.0%
o 2000
16.7%
t 2000
16.7%
S 1000
 
8.3%
l 1000
 
8.3%
c 1000
 
8.3%
a 1000
 
8.3%
n 1000
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11000
91.7%
Uppercase Letter 1000
 
8.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 3000
27.3%
o 2000
18.2%
t 2000
18.2%
l 1000
 
9.1%
c 1000
 
9.1%
a 1000
 
9.1%
n 1000
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
S 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 3000
25.0%
o 2000
16.7%
t 2000
16.7%
S 1000
 
8.3%
l 1000
 
8.3%
c 1000
 
8.3%
a 1000
 
8.3%
n 1000
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 3000
25.0%
o 2000
16.7%
t 2000
16.7%
S 1000
 
8.3%
l 1000
 
8.3%
c 1000
 
8.3%
a 1000
 
8.3%
n 1000
 
8.3%
Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size81.5 KiB
2023-12-09T21:25:55.560954image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length36
Median length34
Mean length26.369
Min length5

Characters and Unicode

Total characters26369
Distinct characters24
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGoods
2nd rowGoods and Services
3rd rowGoods and Services
4th rowServices (other than human services)
5th rowConstruction/Construction Services
ValueCountFrequency (%)
services 1030
38.0%
construction/construction 346
 
12.7%
goods 314
 
11.6%
human 264
 
9.7%
other 223
 
8.2%
than 223
 
8.2%
and 121
 
4.5%
construction 76
 
2.8%
related 76
 
2.8%
services/client 41
 
1.5%
2023-12-09T21:25:55.871803image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2558
9.7%
o 2387
 
9.1%
s 2376
 
9.0%
n 2185
 
8.3%
t 2099
 
8.0%
r 2062
 
7.8%
i 1880
 
7.1%
c 1839
 
7.0%
1714
 
6.5%
v 1071
 
4.1%
Other values (14) 6198
23.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21734
82.4%
Uppercase Letter 2088
 
7.9%
Space Separator 1714
 
6.5%
Other Punctuation 387
 
1.5%
Open Punctuation 223
 
0.8%
Close Punctuation 223
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2558
11.8%
o 2387
11.0%
s 2376
10.9%
n 2185
10.1%
t 2099
9.7%
r 2062
9.5%
i 1880
8.7%
c 1839
8.5%
v 1071
4.9%
u 1032
4.7%
Other values (5) 2245
10.3%
Uppercase Letter
ValueCountFrequency (%)
S 848
40.6%
C 809
38.7%
G 314
 
15.0%
R 76
 
3.6%
H 41
 
2.0%
Space Separator
ValueCountFrequency (%)
1714
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 387
100.0%
Open Punctuation
ValueCountFrequency (%)
( 223
100.0%
Close Punctuation
ValueCountFrequency (%)
) 223
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23822
90.3%
Common 2547
 
9.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2558
10.7%
o 2387
10.0%
s 2376
10.0%
n 2185
9.2%
t 2099
8.8%
r 2062
8.7%
i 1880
7.9%
c 1839
7.7%
v 1071
 
4.5%
u 1032
 
4.3%
Other values (10) 4333
18.2%
Common
ValueCountFrequency (%)
1714
67.3%
/ 387
 
15.2%
( 223
 
8.8%
) 223
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26369
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2558
9.7%
o 2387
 
9.1%
s 2376
 
9.0%
n 2185
 
8.3%
t 2099
 
8.0%
r 2062
 
7.8%
i 1880
 
7.1%
c 1839
 
7.0%
1714
 
6.5%
v 1071
 
4.1%
Other values (14) 6198
23.5%
Distinct985
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size124.0 KiB
2023-12-09T21:25:56.195479image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length247
Median length123
Mean length69.821
Min length6

Characters and Unicode

Total characters69821
Distinct characters77
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique971 ?
Unique (%)97.1%

Sample

1st rowSMD_Materials Channel, Runners & Clips
2nd rowRequirements Contract for Office Supplies
3rd rowCorrection: Architectural Design and Related Consulting Services, Science Park and Research Campus (Sparc) Kips Bay
4th rowBid Extension: BUILDING MANAGEMENT SERVICES
5th rowBid Extension: William McCray Playground Reconstruction
ValueCountFrequency (%)
324
 
3.6%
and 307
 
3.4%
bid 293
 
3.3%
extension 276
 
3.1%
for 241
 
2.7%
of 238
 
2.7%
services 214
 
2.4%
the 110
 
1.2%
at 108
 
1.2%
in 93
 
1.0%
Other values (2616) 6706
75.3%
2023-12-09T21:25:56.697728image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7943
 
11.4%
e 3660
 
5.2%
n 3157
 
4.5%
i 2981
 
4.3%
t 2728
 
3.9%
o 2699
 
3.9%
r 2436
 
3.5%
a 2378
 
3.4%
E 2349
 
3.4%
s 1999
 
2.9%
Other values (67) 37491
53.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 30835
44.2%
Uppercase Letter 23769
34.0%
Space Separator 7943
 
11.4%
Decimal Number 4616
 
6.6%
Other Punctuation 1096
 
1.6%
Dash Punctuation 1000
 
1.4%
Connector Punctuation 234
 
0.3%
Close Punctuation 152
 
0.2%
Open Punctuation 152
 
0.2%
Control 18
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3660
11.9%
n 3157
10.2%
i 2981
9.7%
t 2728
8.8%
o 2699
8.8%
r 2436
 
7.9%
a 2378
 
7.7%
s 1999
 
6.5%
c 1257
 
4.1%
l 1207
 
3.9%
Other values (16) 6333
20.5%
Uppercase Letter
ValueCountFrequency (%)
E 2349
 
9.9%
R 1946
 
8.2%
S 1945
 
8.2%
C 1592
 
6.7%
A 1567
 
6.6%
T 1536
 
6.5%
I 1513
 
6.4%
O 1469
 
6.2%
N 1465
 
6.2%
B 1175
 
4.9%
Other values (16) 7212
30.3%
Decimal Number
ValueCountFrequency (%)
0 1152
25.0%
2 878
19.0%
3 502
10.9%
1 452
 
9.8%
8 396
 
8.6%
5 316
 
6.8%
4 297
 
6.4%
6 279
 
6.0%
7 189
 
4.1%
9 155
 
3.4%
Other Punctuation
ValueCountFrequency (%)
: 438
40.0%
, 330
30.1%
/ 121
 
11.0%
& 103
 
9.4%
. 73
 
6.7%
@ 13
 
1.2%
' 9
 
0.8%
# 9
 
0.8%
Space Separator
ValueCountFrequency (%)
7943
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1000
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 234
100.0%
Close Punctuation
ValueCountFrequency (%)
) 152
100.0%
Open Punctuation
ValueCountFrequency (%)
( 152
100.0%
Control
ValueCountFrequency (%)
 18
100.0%
Math Symbol
ValueCountFrequency (%)
+ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 54604
78.2%
Common 15217
 
21.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3660
 
6.7%
n 3157
 
5.8%
i 2981
 
5.5%
t 2728
 
5.0%
o 2699
 
4.9%
r 2436
 
4.5%
a 2378
 
4.4%
E 2349
 
4.3%
s 1999
 
3.7%
R 1946
 
3.6%
Other values (42) 28271
51.8%
Common
ValueCountFrequency (%)
7943
52.2%
0 1152
 
7.6%
- 1000
 
6.6%
2 878
 
5.8%
3 502
 
3.3%
1 452
 
3.0%
: 438
 
2.9%
8 396
 
2.6%
, 330
 
2.2%
5 316
 
2.1%
Other values (15) 1810
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69821
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7943
 
11.4%
e 3660
 
5.2%
n 3157
 
4.5%
i 2981
 
4.3%
t 2728
 
3.9%
o 2699
 
3.9%
r 2436
 
3.5%
a 2378
 
3.4%
E 2349
 
3.4%
s 1999
 
2.9%
Other values (67) 37491
53.7%
Distinct15
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
2023-12-09T21:25:56.915801image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length47
Median length23
Mean length22.939
Min length5

Characters and Unicode

Total characters22939
Distinct characters34
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st rowCompetitive Sealed Bids
2nd rowCompetitive Sealed Bids
3rd rowRequest for Proposals
4th rowCompetitive Sealed Bids
5th rowCompetitive Sealed Bids
ValueCountFrequency (%)
competitive 748
25.3%
sealed 748
25.3%
bids 625
21.1%
proposals 262
 
8.9%
request 213
 
7.2%
for 213
 
7.2%
quote 28
 
0.9%
information 19
 
0.6%
other 18
 
0.6%
qualifications 14
 
0.5%
Other values (15) 68
 
2.3%
2023-12-09T21:25:57.253893image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 3527
15.4%
i 2258
 
9.8%
1956
 
8.5%
t 1827
 
8.0%
o 1616
 
7.0%
s 1418
 
6.2%
d 1399
 
6.1%
a 1092
 
4.8%
l 1058
 
4.6%
p 1019
 
4.4%
Other values (24) 5769
25.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18188
79.3%
Uppercase Letter 2769
 
12.1%
Space Separator 1956
 
8.5%
Other Punctuation 13
 
0.1%
Dash Punctuation 13
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3527
19.4%
i 2258
12.4%
t 1827
10.0%
o 1616
8.9%
s 1418
7.8%
d 1399
 
7.7%
a 1092
 
6.0%
l 1058
 
5.8%
p 1019
 
5.6%
m 771
 
4.2%
Other values (10) 2203
12.1%
Uppercase Letter
ValueCountFrequency (%)
S 763
27.6%
C 750
27.1%
B 632
22.8%
P 291
 
10.5%
R 213
 
7.7%
Q 55
 
2.0%
I 22
 
0.8%
O 18
 
0.7%
L 13
 
0.5%
N 6
 
0.2%
Space Separator
ValueCountFrequency (%)
1956
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20957
91.4%
Common 1982
 
8.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3527
16.8%
i 2258
10.8%
t 1827
 
8.7%
o 1616
 
7.7%
s 1418
 
6.8%
d 1399
 
6.7%
a 1092
 
5.2%
l 1058
 
5.0%
p 1019
 
4.9%
m 771
 
3.7%
Other values (21) 4972
23.7%
Common
ValueCountFrequency (%)
1956
98.7%
/ 13
 
0.7%
- 13
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22939
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 3527
15.4%
i 2258
 
9.8%
1956
 
8.5%
t 1827
 
8.0%
o 1616
 
7.0%
s 1418
 
6.2%
d 1399
 
6.1%
a 1092
 
4.8%
l 1058
 
4.6%
p 1019
 
4.4%
Other values (24) 5769
25.1%

section_name
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.5 KiB
2023-12-09T21:25:57.423577image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters11000
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowProcurement
2nd rowProcurement
3rd rowProcurement
4th rowProcurement
5th rowProcurement
ValueCountFrequency (%)
procurement 1000
100.0%
2023-12-09T21:25:57.691074image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 2000
18.2%
e 2000
18.2%
P 1000
9.1%
o 1000
9.1%
c 1000
9.1%
u 1000
9.1%
m 1000
9.1%
n 1000
9.1%
t 1000
9.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10000
90.9%
Uppercase Letter 1000
 
9.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 2000
20.0%
e 2000
20.0%
o 1000
10.0%
c 1000
10.0%
u 1000
10.0%
m 1000
10.0%
n 1000
10.0%
t 1000
10.0%
Uppercase Letter
ValueCountFrequency (%)
P 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 2000
18.2%
e 2000
18.2%
P 1000
9.1%
o 1000
9.1%
c 1000
9.1%
u 1000
9.1%
m 1000
9.1%
n 1000
9.1%
t 1000
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 2000
18.2%
e 2000
18.2%
P 1000
9.1%
o 1000
9.1%
c 1000
9.1%
u 1000
9.1%
m 1000
9.1%
n 1000
9.1%
t 1000
9.1%
Distinct4
Distinct (%)3.2%
Missing874
Missing (%)87.4%
Memory size41.0 KiB
2023-12-09T21:25:57.890731image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length60
Median length60
Mean length53.04761905
Min length35

Characters and Unicode

Total characters6684
Distinct characters33
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOther (Describe below in Other Legally Mandated Information)
2nd rowOther (Describe below in Other Legally Mandated Information)
3rd rowOther (Describe below in Other Legally Mandated Information)
4th rowOther (Describe below in Other Legally Mandated Information)
5th rowOther (Describe below in Other Legally Mandated Information)
ValueCountFrequency (%)
other 160
18.2%
in 115
13.1%
below 80
9.1%
legally 80
9.1%
mandated 80
9.1%
information 80
9.1%
describe 80
9.1%
judgment 35
 
4.0%
required 35
 
4.0%
evaluating 35
 
4.0%
Other values (13) 101
11.5%
2023-12-09T21:25:58.216029image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
755
 
11.3%
e 745
 
11.1%
n 459
 
6.9%
a 458
 
6.9%
r 439
 
6.6%
t 406
 
6.1%
i 387
 
5.8%
l 342
 
5.1%
o 339
 
5.1%
d 238
 
3.6%
Other values (23) 2116
31.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5243
78.4%
Space Separator 755
 
11.3%
Uppercase Letter 526
 
7.9%
Close Punctuation 80
 
1.2%
Open Punctuation 80
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 745
14.2%
n 459
 
8.8%
a 458
 
8.7%
r 439
 
8.4%
t 406
 
7.7%
i 387
 
7.4%
l 342
 
6.5%
o 339
 
6.5%
d 238
 
4.5%
s 172
 
3.3%
Other values (12) 1258
24.0%
Uppercase Letter
ValueCountFrequency (%)
O 160
30.4%
I 80
15.2%
L 80
15.2%
M 80
15.2%
D 80
15.2%
J 35
 
6.7%
A 7
 
1.3%
S 4
 
0.8%
Space Separator
ValueCountFrequency (%)
755
100.0%
Close Punctuation
ValueCountFrequency (%)
) 80
100.0%
Open Punctuation
ValueCountFrequency (%)
( 80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5769
86.3%
Common 915
 
13.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 745
12.9%
n 459
 
8.0%
a 458
 
7.9%
r 439
 
7.6%
t 406
 
7.0%
i 387
 
6.7%
l 342
 
5.9%
o 339
 
5.9%
d 238
 
4.1%
s 172
 
3.0%
Other values (20) 1784
30.9%
Common
ValueCountFrequency (%)
755
82.5%
) 80
 
8.7%
( 80
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6684
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
755
 
11.3%
e 745
 
11.1%
n 459
 
6.9%
a 458
 
6.9%
r 439
 
6.6%
t 406
 
6.1%
i 387
 
5.8%
l 342
 
5.1%
o 339
 
5.1%
d 238
 
3.6%
Other values (23) 2116
31.7%

pin
Text

MISSING 

Distinct945
Distinct (%)97.9%
Missing35
Missing (%)3.5%
Memory size63.8 KiB
2023-12-09T21:25:58.547749image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length20
Median length10
Mean length9.460103627
Min length4

Characters and Unicode

Total characters9129
Distinct characters63
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique927 ?
Unique (%)96.1%

Sample

1st row493046
2nd rowB5830040
3rd row100860001
4th row06824B0003
5th row84623B0084
ValueCountFrequency (%)
sca 17
 
1.6%
epin 5
 
0.5%
5
 
0.5%
rfp 4
 
0.4%
2023 4
 
0.4%
81622p0003 3
 
0.3%
81622p0004 3
 
0.3%
857 3
 
0.3%
mhp 3
 
0.3%
23 3
 
0.3%
Other values (964) 987
95.2%
2023-12-09T21:25:59.038477image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1936
21.2%
2 1375
15.1%
3 779
8.5%
8 700
 
7.7%
1 618
 
6.8%
4 556
 
6.1%
5 477
 
5.2%
6 460
 
5.0%
B 451
 
4.9%
7 379
 
4.2%
Other values (53) 1398
15.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7558
82.8%
Uppercase Letter 1144
 
12.5%
Dash Punctuation 253
 
2.8%
Space Separator 72
 
0.8%
Lowercase Letter 72
 
0.8%
Other Punctuation 23
 
0.3%
Open Punctuation 5
 
0.1%
Connector Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 451
39.4%
P 153
 
13.4%
S 89
 
7.8%
C 70
 
6.1%
A 58
 
5.1%
D 54
 
4.7%
R 45
 
3.9%
M 32
 
2.8%
I 27
 
2.4%
L 18
 
1.6%
Other values (15) 147
 
12.8%
Lowercase Letter
ValueCountFrequency (%)
t 10
13.9%
r 9
12.5%
e 8
11.1%
a 7
9.7%
i 6
8.3%
n 5
 
6.9%
s 4
 
5.6%
o 4
 
5.6%
u 4
 
5.6%
d 2
 
2.8%
Other values (8) 13
18.1%
Decimal Number
ValueCountFrequency (%)
0 1936
25.6%
2 1375
18.2%
3 779
10.3%
8 700
 
9.3%
1 618
 
8.2%
4 556
 
7.4%
5 477
 
6.3%
6 460
 
6.1%
7 379
 
5.0%
9 278
 
3.7%
Other Punctuation
ValueCountFrequency (%)
# 8
34.8%
, 6
26.1%
: 5
21.7%
/ 3
 
13.0%
. 1
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 253
100.0%
Space Separator
ValueCountFrequency (%)
72
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7913
86.7%
Latin 1216
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 451
37.1%
P 153
 
12.6%
S 89
 
7.3%
C 70
 
5.8%
A 58
 
4.8%
D 54
 
4.4%
R 45
 
3.7%
M 32
 
2.6%
I 27
 
2.2%
L 18
 
1.5%
Other values (33) 219
18.0%
Common
ValueCountFrequency (%)
0 1936
24.5%
2 1375
17.4%
3 779
9.8%
8 700
 
8.8%
1 618
 
7.8%
4 556
 
7.0%
5 477
 
6.0%
6 460
 
5.8%
7 379
 
4.8%
9 278
 
3.5%
Other values (10) 355
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9129
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1936
21.2%
2 1375
15.1%
3 779
8.5%
8 700
 
7.7%
1 618
 
6.8%
4 556
 
6.1%
5 477
 
5.2%
6 460
 
5.0%
B 451
 
4.9%
7 379
 
4.2%
Other values (53) 1398
15.3%
Distinct690
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
2023-12-09T21:25:59.290642image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters23000
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique503 ?
Unique (%)50.3%

Sample

1st row2023-11-30T10:00:00.000
2nd row2024-01-03T16:00:00.000
3rd row2024-01-08T23:59:00.000
4th row2023-11-27T00:00:00.000
5th row2023-12-05T10:30:00.000
ValueCountFrequency (%)
2023-11-28t10:30:00.000 7
 
0.7%
2023-04-04t11:00:00.000 7
 
0.7%
2023-04-24t14:00:00.000 6
 
0.6%
2023-05-16t10:30:00.000 6
 
0.6%
2023-07-18t14:00:00.000 6
 
0.6%
2023-11-14t10:30:00.000 5
 
0.5%
2023-10-03t10:30:00.000 5
 
0.5%
2023-05-11t11:00:00.000 5
 
0.5%
2023-02-16t10:30:00.000 5
 
0.5%
2023-04-11t10:30:00.000 5
 
0.5%
Other values (680) 943
94.3%
2023-12-09T21:25:59.656702image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9289
40.4%
2 2593
 
11.3%
- 2000
 
8.7%
: 2000
 
8.7%
1 1918
 
8.3%
3 1517
 
6.6%
T 1000
 
4.3%
. 1000
 
4.3%
4 372
 
1.6%
6 325
 
1.4%
Other values (4) 986
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17000
73.9%
Other Punctuation 3000
 
13.0%
Dash Punctuation 2000
 
8.7%
Uppercase Letter 1000
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9289
54.6%
2 2593
 
15.3%
1 1918
 
11.3%
3 1517
 
8.9%
4 372
 
2.2%
6 325
 
1.9%
5 293
 
1.7%
9 270
 
1.6%
7 221
 
1.3%
8 202
 
1.2%
Other Punctuation
ValueCountFrequency (%)
: 2000
66.7%
. 1000
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2000
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22000
95.7%
Latin 1000
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9289
42.2%
2 2593
 
11.8%
- 2000
 
9.1%
: 2000
 
9.1%
1 1918
 
8.7%
3 1517
 
6.9%
. 1000
 
4.5%
4 372
 
1.7%
6 325
 
1.5%
5 293
 
1.3%
Other values (3) 693
 
3.1%
Latin
ValueCountFrequency (%)
T 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9289
40.4%
2 2593
 
11.3%
- 2000
 
8.7%
: 2000
 
8.7%
1 1918
 
8.3%
3 1517
 
6.6%
T 1000
 
4.3%
. 1000
 
4.3%
4 372
 
1.6%
6 325
 
1.4%
Other values (4) 986
 
4.3%

address_to_request
Text

MISSING 

Distinct162
Distinct (%)26.9%
Missing398
Missing (%)39.8%
Memory size74.6 KiB
2023-12-09T21:25:59.987417image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length196
Median length103
Mean length48.51993355
Min length1

Characters and Unicode

Total characters29209
Distinct characters72
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)17.1%

Sample

1st row90 Church Street, 6th Floor, New York, NY 10007
2nd row65 Court Street, Room 1201, Brooklyn, NY 11201
3rd row.
4th row.
5th row100 Gold Street, 9X, New York, NY 10038
ValueCountFrequency (%)
ny 520
 
10.1%
new 410
 
7.9%
york 410
 
7.9%
floor 381
 
7.4%
street 365
 
7.1%
10007 245
 
4.7%
church 151
 
2.9%
90 151
 
2.9%
6th 139
 
2.7%
1 99
 
1.9%
Other values (244) 2299
44.5%
2023-12-09T21:26:00.507277image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4575
15.7%
e 2036
 
7.0%
o 1855
 
6.4%
r 1818
 
6.2%
t 1767
 
6.0%
0 1731
 
5.9%
, 1574
 
5.4%
1 1322
 
4.5%
N 943
 
3.2%
Y 937
 
3.2%
Other values (62) 10651
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13869
47.5%
Decimal Number 4831
 
16.5%
Space Separator 4575
 
15.7%
Uppercase Letter 4060
 
13.9%
Other Punctuation 1754
 
6.0%
Dash Punctuation 116
 
0.4%
Connector Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2036
14.7%
o 1855
13.4%
r 1818
13.1%
t 1767
12.7%
h 884
 
6.4%
n 729
 
5.3%
l 716
 
5.2%
w 470
 
3.4%
k 464
 
3.3%
s 449
 
3.2%
Other values (16) 2681
19.3%
Uppercase Letter
ValueCountFrequency (%)
N 943
23.2%
Y 937
23.1%
F 446
11.0%
S 444
10.9%
C 401
9.9%
A 141
 
3.5%
T 110
 
2.7%
L 107
 
2.6%
B 104
 
2.6%
I 95
 
2.3%
Other values (16) 332
 
8.2%
Decimal Number
ValueCountFrequency (%)
0 1731
35.8%
1 1322
27.4%
7 359
 
7.4%
3 274
 
5.7%
6 239
 
4.9%
5 226
 
4.7%
9 192
 
4.0%
8 166
 
3.4%
2 165
 
3.4%
4 157
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 1574
89.7%
. 99
 
5.6%
/ 53
 
3.0%
: 13
 
0.7%
@ 10
 
0.6%
; 4
 
0.2%
' 1
 
0.1%
Space Separator
ValueCountFrequency (%)
4575
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17929
61.4%
Common 11280
38.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2036
 
11.4%
o 1855
 
10.3%
r 1818
 
10.1%
t 1767
 
9.9%
N 943
 
5.3%
Y 937
 
5.2%
h 884
 
4.9%
n 729
 
4.1%
l 716
 
4.0%
w 470
 
2.6%
Other values (42) 5774
32.2%
Common
ValueCountFrequency (%)
4575
40.6%
0 1731
 
15.3%
, 1574
 
14.0%
1 1322
 
11.7%
7 359
 
3.2%
3 274
 
2.4%
6 239
 
2.1%
5 226
 
2.0%
9 192
 
1.7%
8 166
 
1.5%
Other values (10) 622
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29209
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4575
15.7%
e 2036
 
7.0%
o 1855
 
6.4%
r 1818
 
6.2%
t 1767
 
6.0%
0 1731
 
5.9%
, 1574
 
5.4%
1 1322
 
4.5%
N 943
 
3.2%
Y 937
 
3.2%
Other values (62) 10651
36.5%

contact_name
Text

MISSING 

Distinct199
Distinct (%)30.8%
Missing353
Missing (%)35.3%
Memory size56.4 KiB
2023-12-09T21:26:00.842791image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length50
Median length47
Mean length14.66306028
Min length7

Characters and Unicode

Total characters9487
Distinct characters59
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)17.9%

Sample

1st rowChenezza Graham-Ramirez
2nd rowVendor Hotline
3rd rowSPARC Design RFP Team
4th rowSI Ferry Advertising Team
5th rowBenjamin Palevsky
ValueCountFrequency (%)
lucero 30
 
2.1%
lee 30
 
2.1%
dawn 26
 
1.8%
team 25
 
1.8%
lewis 21
 
1.5%
raymond 21
 
1.5%
evelyn 21
 
1.5%
randy 21
 
1.5%
vendor 20
 
1.4%
hotline 20
 
1.4%
Other values (380) 1191
83.5%
2023-12-09T21:26:01.330614image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 910
 
9.6%
e 905
 
9.5%
811
 
8.5%
n 763
 
8.0%
i 573
 
6.0%
r 492
 
5.2%
o 428
 
4.5%
l 396
 
4.2%
s 309
 
3.3%
h 280
 
3.0%
Other values (49) 3620
38.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6961
73.4%
Uppercase Letter 1666
 
17.6%
Space Separator 811
 
8.5%
Other Punctuation 24
 
0.3%
Dash Punctuation 22
 
0.2%
Decimal Number 2
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 910
13.1%
e 905
13.0%
n 763
11.0%
i 573
 
8.2%
r 492
 
7.1%
o 428
 
6.1%
l 396
 
5.7%
s 309
 
4.4%
h 280
 
4.0%
t 246
 
3.5%
Other values (16) 1659
23.8%
Uppercase Letter
ValueCountFrequency (%)
L 165
 
9.9%
R 136
 
8.2%
S 127
 
7.6%
C 121
 
7.3%
D 111
 
6.7%
M 88
 
5.3%
A 86
 
5.2%
H 81
 
4.9%
F 80
 
4.8%
G 70
 
4.2%
Other values (16) 601
36.1%
Other Punctuation
ValueCountFrequency (%)
. 19
79.2%
, 3
 
12.5%
@ 2
 
8.3%
Space Separator
ValueCountFrequency (%)
811
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8627
90.9%
Common 860
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 910
 
10.5%
e 905
 
10.5%
n 763
 
8.8%
i 573
 
6.6%
r 492
 
5.7%
o 428
 
5.0%
l 396
 
4.6%
s 309
 
3.6%
h 280
 
3.2%
t 246
 
2.9%
Other values (42) 3325
38.5%
Common
ValueCountFrequency (%)
811
94.3%
- 22
 
2.6%
. 19
 
2.2%
, 3
 
0.3%
1 2
 
0.2%
@ 2
 
0.2%
_ 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9487
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 910
 
9.6%
e 905
 
9.5%
811
 
8.5%
n 763
 
8.0%
i 573
 
6.0%
r 492
 
5.2%
o 428
 
4.5%
l 396
 
4.2%
s 309
 
3.3%
h 280
 
3.0%
Other values (49) 3620
38.2%

contact_phone
Text

MISSING 

Distinct162
Distinct (%)26.3%
Missing385
Missing (%)38.5%
Memory size54.8 KiB
2023-12-09T21:26:01.609171image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters8610
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)13.2%

Sample

1st row(212) 306-4684
2nd row(718) 935-2300
3rd row(212) 618-1236
4th row(212) 618-1236
5th row(212) 863-5147
ValueCountFrequency (%)
212 383
31.1%
718 163
 
13.3%
472-8367 21
 
1.7%
386-0409 21
 
1.7%
646 21
 
1.7%
935-2300 20
 
1.6%
815-3245 19
 
1.5%
306-3127 18
 
1.5%
312-3649 17
 
1.4%
306-4521 17
 
1.4%
Other values (165) 530
43.1%
2023-12-09T21:26:02.003342image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1205
14.0%
3 844
9.8%
1 783
9.1%
( 615
 
7.1%
) 615
 
7.1%
615
 
7.1%
- 615
 
7.1%
0 608
 
7.1%
6 562
 
6.5%
8 522
 
6.1%
Other values (4) 1626
18.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6150
71.4%
Open Punctuation 615
 
7.1%
Close Punctuation 615
 
7.1%
Space Separator 615
 
7.1%
Dash Punctuation 615
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1205
19.6%
3 844
13.7%
1 783
12.7%
0 608
9.9%
6 562
9.1%
8 522
8.5%
4 516
8.4%
5 413
 
6.7%
7 396
 
6.4%
9 301
 
4.9%
Open Punctuation
ValueCountFrequency (%)
( 615
100.0%
Close Punctuation
ValueCountFrequency (%)
) 615
100.0%
Space Separator
ValueCountFrequency (%)
615
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 615
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8610
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1205
14.0%
3 844
9.8%
1 783
9.1%
( 615
 
7.1%
) 615
 
7.1%
615
 
7.1%
- 615
 
7.1%
0 608
 
7.1%
6 562
 
6.5%
8 522
 
6.1%
Other values (4) 1626
18.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8610
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1205
14.0%
3 844
9.8%
1 783
9.1%
( 615
 
7.1%
) 615
 
7.1%
615
 
7.1%
- 615
 
7.1%
0 608
 
7.1%
6 562
 
6.5%
8 522
 
6.1%
Other values (4) 1626
18.9%

email
Text

MISSING 

Distinct208
Distinct (%)31.8%
Missing346
Missing (%)34.6%
Memory size62.8 KiB
2023-12-09T21:26:02.331029image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length88
Median length48
Mean length24.14220183
Min length12

Characters and Unicode

Total characters15789
Distinct characters39
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique128 ?
Unique (%)19.6%

Sample

1st rowchenezza.graham-ramirez@nycha.nyc.gov
2nd rowvendorhotline@schools.nyc.gov
3rd rowsparcdesign@edc
4th rowsiferryadvertising@edc.nyc
5th rowjerseystreetrfp@hpd.nyc.gov;palevskb@hpd.nyc.gov
ValueCountFrequency (%)
rfp.procurement@nycha.nyc.gov 32
 
4.8%
elucero@dcas.nyc.gov 22
 
3.3%
rlewis@nycsca.org 21
 
3.1%
leer31@nychhc.org 21
 
3.1%
vendorhotline@schools.nyc.gov 20
 
3.0%
shawntae.davis@nycha.nyc.gov 18
 
2.7%
albina.zulkasheva@nycha.nyc.gov 16
 
2.4%
vpersaud@nycsca.org 16
 
2.4%
dhendricks@nycsca.org 15
 
2.2%
suksingh@dcas.nyc.gov 14
 
2.1%
Other values (197) 478
71.0%
2023-12-09T21:26:02.824487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 1401
 
8.9%
n 1362
 
8.6%
. 1336
 
8.5%
o 1115
 
7.1%
a 1063
 
6.7%
r 932
 
5.9%
e 919
 
5.8%
y 888
 
5.6%
g 783
 
5.0%
s 729
 
4.6%
Other values (29) 5261
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13630
86.3%
Other Punctuation 2034
 
12.9%
Decimal Number 70
 
0.4%
Space Separator 20
 
0.1%
Connector Punctuation 18
 
0.1%
Dash Punctuation 17
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 1401
 
10.3%
n 1362
 
10.0%
o 1115
 
8.2%
a 1063
 
7.8%
r 932
 
6.8%
e 919
 
6.7%
y 888
 
6.5%
g 783
 
5.7%
s 729
 
5.3%
v 548
 
4.0%
Other values (16) 3890
28.5%
Decimal Number
ValueCountFrequency (%)
3 26
37.1%
1 24
34.3%
2 12
17.1%
0 5
 
7.1%
4 2
 
2.9%
5 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 1336
65.7%
@ 676
33.2%
; 20
 
1.0%
, 2
 
0.1%
Space Separator
ValueCountFrequency (%)
20
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13630
86.3%
Common 2159
 
13.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 1401
 
10.3%
n 1362
 
10.0%
o 1115
 
8.2%
a 1063
 
7.8%
r 932
 
6.8%
e 919
 
6.7%
y 888
 
6.5%
g 783
 
5.7%
s 729
 
5.3%
v 548
 
4.0%
Other values (16) 3890
28.5%
Common
ValueCountFrequency (%)
. 1336
61.9%
@ 676
31.3%
3 26
 
1.2%
1 24
 
1.1%
; 20
 
0.9%
20
 
0.9%
_ 18
 
0.8%
- 17
 
0.8%
2 12
 
0.6%
0 5
 
0.2%
Other values (3) 5
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15789
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 1401
 
8.9%
n 1362
 
8.6%
. 1336
 
8.5%
o 1115
 
7.1%
a 1063
 
6.7%
r 932
 
5.9%
e 919
 
5.8%
y 888
 
5.6%
g 783
 
5.0%
s 729
 
4.6%
Other values (29) 5261
33.3%

contract_amount
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

contact_fax
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB
Distinct932
Distinct (%)95.3%
Missing22
Missing (%)2.2%
Memory size1.4 MiB
2023-12-09T21:26:03.252084image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8237
Median length1601
Mean length1390.131902
Min length38

Characters and Unicode

Total characters1359549
Distinct characters94
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique909 ?
Unique (%)92.9%

Sample

1st row<p>The materials to be provided by the successful vendor are described in greater detail in the RFQ Number. Interested vendors are invited to obtain a copy of the opportunity at NYCHAs website by going to the http://www.nyc.gov/nychabusiness. On the left side, click on iSupplier Vendor Registration/Login link. 1. If you have an iSupplier account, then click on the Login for registered vendors link and sign into your iSupplier account. (2) If you do not have an iSupplier account you can Request an account by clicking on New suppliers register in iSupplier to apply for log-in credentials. Once you have accessed your iSupplier account, log into your account, then choose under the Oracle Financials home page, the menu option Sourcing Supplier, then choose Sourcing, then choose Sourcing Homepage; and conduct a search in the Search Open Negotiations box for RFQ Number. Please see details regarding the RFQ below:</p><p>RFQ Number: 493046 Title: SMD_Materials Channel, Runners & Clips Location: VARIOUS DEVELOPMENTS LOCATED IN ALL FIVE (5) BOROUGHS OF NEW YORK CITY </p>
2nd row<p><u><strong>Please note that bids are due via electronic mail to DCPSubmissions@schools.nyc.gov</strong></u>. To download, please go to https://infohub.nyced.org/resources/vendors/open-doe-solicitations/request-for-bids. If you cannot download, send an e-mail to vendorhotline@schools.nyc.gov with the RFB number and title in the subject line.</p><p>For all questions related to this RFB, please e-mail Sladolc@schools.nyc.gov with the RFB number and title in the subject line of your e-mail.</p><p>Description: This is a requirements contract for furnishing and delivering Office Supplies, to over 1,800 schools and offices under the jurisdiction of the Board of Education of the City School District of the City of New York (Board of Education, NYCDOE, NYCBOE,DOE, BOE or the Board). <u><strong>A Pre-Bid conference will be held on December 6, 2023, 11:00A.M</strong></u>. at 65 Court Street, Room 1201, Brooklyn, NY 11201. Attendance to the pre-bid conference is optional. Due to space limitations, we ask that no more than 2 representatives of your company attend. If you intend to attend the pre-bid conference, please email Steve Ladolcetta Sladolc@schools.nyc.gov by close of business on December 1, 2023 with the name of representative that will be attending.</p><p><u><strong>For electronic bid submissions, please note the following procedures: </strong></u>Bid submissions must be sent via electronic mail (The Bid Submission Email) to DCPSubmissions@schools.nyc.gov (the Bid Submission Email Address). Bid Submissions sent to any other email address will be disregarded. The subject line of your Bid Submission Email must include the solicitation number and the name of the submitting vendor (e.g. B5830  Enter Company Name). Please attach the completed Request for Bids and the Bid Blank documents to the Bid Submission Email as separate files. Please name the bid blank attachment Bid Blank and the completed Request for Bids attachment RFB. If the files accompanying your bid submission are too large to be transmitted as email attachments, please include in the first line of your Bid Submission Email a link to a Microsoft OneDrive folder containing all of your bid-related documents. Please note that if you are using OneDrive, do not attach any documents to the Bid Submission Email. Further, please include a separate folder within your OneDrive folder which includes the separate bid blank file. Please name this folder and the bid blank file Bid Blank. The name of your OneDrive folder must match the subject line of your bid submission, and your OneDrive folder must not contain any files unrelated to the Bid Submission.</p><p><u><strong>Guidance for first-time Microsoft One-Drive Users:</strong></u> Microsoft OneDrive (OneDrive) is a file hosting and synchronization service operated by Microsoft as part of its web version of Microsoft Office. OneDrive allows users to grant access to files which are too large to transmit via electronic mail to other users. If you do not have Office 365, please take the following steps to gain access to a free version of OneDrive so that you can upload those bid submission documents which are too large to transmit via electronic mail: 1. Conduct an internet search for Microsoft OneDrive; 2. Navigate to the official Microsoft website and sign up for a free account; 3. Once you have created a folder for the solicitation whose name matches the subject line of your Bid Submission Email, upload the documents relevant to your bid submission in this folder. 4. Create a share link for this folder; 5. Be sure to check your share settings so that anyone receiving the link that you create will be able to open the link and access the files. If your share link permissions are restricted (e.g. to only your organization in Office 365), the DOE will not be able to view your solicitation documents. It is your responsibility to ensure that the link(s) you provide allows the DOE to view, download and/or open your documents; and 6. Include the link which you have created as the first line of your Bid Submission Email. The Bid opening will be conducted virtually via Microsoft Teams on Thursday, January 4, 2024 at 11:00 A.M. Bidders who have submitted their Bid Submission Email by the Bid Submission Deadline will receive a reply to their Bid Submission Email with a link to be able to view a livestream of the Bid opening online. If you do not receive a confirmation email of the DOEs receipt of your electronic bid submission, please email: Gabriel Soriano at GSorian@schools.nyc.gov.</p><p><u><strong>For hard copy (paper) bid submissions, please follow the below instructions:</strong></u> Further to prior instructions regarding submissions of bids. In addition to electronic submission via email, Bidders may choose to hand deliver their bid packages to NYC DOE at any time prior to the Bid Due Date/Time. If you plan to submit a paper bid, you must provide notice by e-mailing DCPSubmissions@schools.nyc.gov, including Paper Submission Request for Solicitation # B5830 in the subject line, at least three (3) business days in advance of the anticipated date and time and place you or your agent plan to arrive at 65 Court Street, Brooklyn, NY 11201, Rm 1201 to drop off your bid. Bidders should include in their notification e-mail the name of the person who will be delivering the bid or advise that the Bid Package will be arriving by messenger. Bidders who fail to provide advance notification of intent to hand-deliver a bid risk not having anyone to receive the bid.</p><p>Please continue to check the DOE website and/or Vendor Portal for updates. https://infohub.nyced.org/vendors https://www.finance360.org/vendor/vendorportal/</p><p>BID OPENS VIRTUALLY ON January 4, 2024 AT 11:00 A.M.  PLEASE SEE VIRTUAL LINK BELOW:</p><p>https://teams.microsoft.com/l/meetup-join/19%3ameeting_ZTUyMjRkYzQtNGUxYy00ZmFkLWEyY2MtOGY5N2E5YWU2Yzdi%40thread.v2/0?context=%7B%22Tid%22%3A%2218492cb7-ef45-4561-8571-0c42e5f7ac07%22%2C%22Oid%22%3A%2233f73cb2-8a8c-4d65-8f37-5256f643d9ed%22%2C%22IsBroadcastMeeting%22%3Atrue%2C%22role%22%3A%22a%22%7D&btype=a&role=a</p><p> </p>
3rd row<p>The New York City Economic Development Corporation (NYCEDC) is seeking a consultant team to provide Architectural, Engineering, Landscape design, and Related consulting services to design a new Science Park and Research Campus (SPARC) in Kips Bay. The SPARC Kips Bay Project will consist of approximately 756,200 gross square feet of new construction on the site, including: modern academic space for City University of New York, a New York City Public Schools high school, vibrant public spaces, a pedestrian bridge, and resiliency infrastructure.</p><p>NYCEDC plans to select a consultant on the basis of factors stated in the RFP which include, but are not limited to: the quality of the proposal, experience of key staff identified in the proposal, experience and quality of any subcontractors proposed, demonstrated successful experience in performing services similar to those encompassed in the RFP, ability to meet M/WBE Participation Goals, and the proposed fee.</p><p>It is the policy of NYCEDC to comply with all federal, state and City laws and regulations which prohibit unlawful discrimination because of race, creed, color, national origin, sex, age, disability, marital status and other protected category and to take affirmative action in working with contracting parties to ensure certified Minority and Women-owned Business Enterprises (MWBEs) share in the economic opportunities generated by NYCEDCs projects and initiatives. Please refer to the Equal Employment and Affirmative Compliance for Non-Construction Contracts Addendum in the RFP.</p><p>This project has Minority and Women Owned Business Enterprise (M/WBE) participation goals, and all respondents will be required to submit an M/WBE Participation Proposal with their response. To learn more about NYCEDCs M/WBE program, visit http://edc.nyc/opportunity-mwdbe. For the list of companies who have been certified with New York City as M/WBEs, please go to the Department of Small Business online directory of certified firms at https://sbsconnect.nyc.gov/certification-directory-search/.</p><p>NYCEDC established the Contract Financing Loan Fund programs for Minority, Women and Disadvantaged Business Enterprise (M/W/DBE) interested in working on public construction projects. Contract Financing Loan Fund facilitates financing for short-term mobilization needs such as insurance, labor, supplies and equipment. Bidders/subcontractors are strongly encouraged to visit the NYCEDC website at http://edc.nyc/opportunity-mwdbe to learn more about the program.</p><p>An optional hybrid (in-person and virtual) pre-proposal informational session will be held on Monday, November 27, 2023 at 10:00A.M. at NYCEDC, One Liberty Plaza, New York, NY, 14th floor and through the following link: https://teams.microsoft.com/l/meetupjoin/ 19%3ameeting_YmU1ZWNhYTAtODVkZi00MmVjLTliMzctOWM2NzYxYzZlNGFl%4 0thread.v2/0?context=%7b%22Tid%22%3a%22f1d4198c-95e0-40fe-bf4a- 3faa2bea4dbd%22%2c%22Oid%22%3a%22dedf2f84-5408-4d23-8602- c6f9e71cb73f%22%7d</p><p>Those who wish to attend should RSVP by email to sparcdesign@edc.nyc on or before November 21, 2023. Respondents may submit questions and/or request clarifications from NYCEDC no later than 11:59 P.M. on Friday, December 1, 2023. Questions regarding the subject matter of this RFP should be directed to sparcdesign@edc.nyc. Answers to all questions will be posted by Monday, December 18, 2023, to https://edc.nyc/rfps. Questions regarding the subject matter of this RFP will not be accepted after 11:59 P.M. on Friday, December 1, 2023, however, technical questions pertaining to downloading and submitting proposals to this RFP may be directed to RFPREQUEST@edc.nyc on or before Monday, January 8, 2024.</p><p>Detailed submission guidelines and requirements are outlined in the RFP, available as of Friday, November 17, 2023. To download a copy of the solicitation documents please visit https://edc.nyc/rfps. RESPONSES ARE DUE NO LATER THAN Monday, January 8, 2024. Please click the link in the Deadlines section of this projects web page (which can be found on https://edc.nyc/rfps) to electronically upload a proposal for this solicitation.</p>
4th row<p>The Administration for Childrens Services (ACS) seeks a contractor to provide Building Management Services for the Nicholas Scopetta Children's Center at 492 First Avenue. Building Management includes all services related to the service and maintenance of the building's physical conditions. This Competitive Sealed Bid will be solicited to the entire Citywide Bidders List. </p><p>Bid Opening: See PASSPort for the most up to date information on date, time, and location. Anticipated Funding and Payment Structure: Anticipated total maximum available funding is $19,621,557.00 Estimated number of contracts: 1 Use of PASSPort: Bids will ONLY be accepted through PASSPort. If you do not have a PASSPort account, please visit www.nyc.gov/passport to get started.</p><p>Questions regarding this CSB must be transmitted in writing to the Agency Contact Person, Alex Linetskiy, at BuildingManagement@acs.nyc.gov. ACS may not respond to questions regarding this CSB that are received less than one week prior to the bid due date. Please submit your bid responses by both acknowledging the receipt of the RFx in the Acknowledgement tab and completing your response in the Manage Responses tab. Vendor resources and materials can be found at https://www1.nyc.gov/site/mocs/systems/passport-user-materials.page. After the Question Deadline, questions regarding this solicitation may not be addressed. If you need additional assistance with PASSPort, please submit an inquiry to the MOCS Service Desk at https://mocssupport.atlassian.net/servicedesk/customer/portal/8 or complete a contact form at https://www1.nyc.gov/site/mocs/contact/contact-form.page</p>
5th row<p>This procurement is subject to: Participation goals for MBEs and/or WBEs as required by Local Law 1 of 2013 Apprenticeship Requirements Bid Submission must be submitted both in PASSPort and by Mail or Drop Box at Olmsted Center Annex, The Olmsted Center, 117-06 Roosevelt Avenue, Flushing NY 11368 Bid Opening will be on November 27, 2023 at 11:30 am via Zoom Link: https://us02web.zoom.us/j/2290435542?pwd=VFovbDl6UTVFNXl3ZGxPYUVsQU5kZz09 Meeting ID: 229 043 5542 Passcode: 763351 One Tap Mobile: +19292056099,,2290435542#,,,,*763351# US (New York) +13017158592,,2290435542#,,,,*763351# US (Washington DC) The Cost Estimate Range is $3,000,000.00 - $5,000,000.00 Bid documents are available online for free through NYC PASSPortSystem http://www1.nyc.gov/site/mocs/systems/about-go-to-passport.page To download the bid solicitation documents (including drawings if any) you must have a NYC ID Account and Login.</p>
ValueCountFrequency (%)
the 11194
 
5.8%
to 7167
 
3.7%
and 4932
 
2.6%
of 4280
 
2.2%
in 2885
 
1.5%
for 2732
 
1.4%
be 2599
 
1.4%
at 2347
 
1.2%
a 2160
 
1.1%
bid 2157
 
1.1%
Other values (10321) 148979
77.8%
2023-12-09T21:26:03.843038image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
190880
 
14.0%
e 112592
 
8.3%
t 88669
 
6.5%
o 81408
 
6.0%
i 76781
 
5.6%
n 69677
 
5.1%
s 66449
 
4.9%
a 64854
 
4.8%
r 61888
 
4.6%
l 39126
 
2.9%
Other values (84) 507225
37.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 948805
69.8%
Space Separator 192375
 
14.1%
Uppercase Letter 97731
 
7.2%
Other Punctuation 45873
 
3.4%
Decimal Number 41743
 
3.1%
Math Symbol 16770
 
1.2%
Dash Punctuation 5454
 
0.4%
Control 4435
 
0.3%
Close Punctuation 2851
 
0.2%
Open Punctuation 2808
 
0.2%
Other values (5) 704
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 112592
11.9%
t 88669
 
9.3%
o 81408
 
8.6%
i 76781
 
8.1%
n 69677
 
7.3%
s 66449
 
7.0%
a 64854
 
6.8%
r 61888
 
6.5%
l 39126
 
4.1%
c 36664
 
3.9%
Other values (18) 250697
26.4%
Uppercase Letter
ValueCountFrequency (%)
P 11210
 
11.5%
S 10115
 
10.3%
C 7684
 
7.9%
A 6922
 
7.1%
T 5913
 
6.1%
R 5577
 
5.7%
N 5173
 
5.3%
B 4991
 
5.1%
E 4623
 
4.7%
F 4582
 
4.7%
Other values (16) 30941
31.7%
Other Punctuation
ValueCountFrequency (%)
. 13919
30.3%
/ 11809
25.7%
, 11499
25.1%
: 4361
 
9.5%
% 1252
 
2.7%
' 731
 
1.6%
@ 684
 
1.5%
# 655
 
1.4%
; 400
 
0.9%
* 249
 
0.5%
Other values (5) 314
 
0.7%
Decimal Number
ValueCountFrequency (%)
0 8539
20.5%
2 8400
20.1%
1 5792
13.9%
3 4883
11.7%
5 3056
 
7.3%
4 2601
 
6.2%
6 2256
 
5.4%
8 2227
 
5.3%
9 2065
 
4.9%
7 1924
 
4.6%
Math Symbol
ValueCountFrequency (%)
< 8124
48.4%
> 8124
48.4%
+ 352
 
2.1%
= 170
 
1.0%
Space Separator
ValueCountFrequency (%)
190880
99.2%
  1495
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 5454
100.0%
Control
ValueCountFrequency (%)
 4435
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2851
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2808
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 356
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 322
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 24
100.0%
Other Symbol
ValueCountFrequency (%)
® 1
100.0%
Other Number
ValueCountFrequency (%)
½ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1046536
77.0%
Common 313013
 
23.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 112592
 
10.8%
t 88669
 
8.5%
o 81408
 
7.8%
i 76781
 
7.3%
n 69677
 
6.7%
s 66449
 
6.3%
a 64854
 
6.2%
r 61888
 
5.9%
l 39126
 
3.7%
c 36664
 
3.5%
Other values (44) 348428
33.3%
Common
ValueCountFrequency (%)
190880
61.0%
. 13919
 
4.4%
/ 11809
 
3.8%
, 11499
 
3.7%
0 8539
 
2.7%
2 8400
 
2.7%
< 8124
 
2.6%
> 8124
 
2.6%
1 5792
 
1.9%
- 5454
 
1.7%
Other values (30) 40473
 
12.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1358037
99.9%
None 1512
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
190880
 
14.1%
e 112592
 
8.3%
t 88669
 
6.5%
o 81408
 
6.0%
i 76781
 
5.7%
n 69677
 
5.1%
s 66449
 
4.9%
a 64854
 
4.8%
r 61888
 
4.6%
l 39126
 
2.9%
Other values (77) 505713
37.2%
None
ValueCountFrequency (%)
  1495
98.9%
ç 7
 
0.5%
· 4
 
0.3%
§ 3
 
0.2%
® 1
 
0.1%
½ 1
 
0.1%
é 1
 
0.1%

additional_description_2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

additional_description_3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

other_info_1
Text

MISSING 

Distinct333
Distinct (%)75.9%
Missing561
Missing (%)56.1%
Memory size180.3 KiB
2023-12-09T21:26:04.456658image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1866
Median length918
Mean length322.0683371
Min length1

Characters and Unicode

Total characters141388
Distinct characters88
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique310 ?
Unique (%)70.6%

Sample

1st rowThe New York City Department of Education (DOE) strives to give all businesses, including Minority and Women-Owned Business Enterprises (MWBEs), an equal opportunity to compete for DOE procurements. The DOEs mission is to provide equal access to procurement opportunities for all qualified vendors, including MWBEs, from all segments of the community. The DOE works to enhance the ability of MWBEs to compete for contracts. DOE is committed to ensuring that MWBEs fully participate in the procurement process.
2nd rowBid opening Location - Online Virtual Bid Opening via Webex Link: https://nycacs.webex.com/nycacs/j.php?MTID=m78e407199db155e8b0ec20283a18ba4a Meeting # 2340 752 5250 +1-646-992-2010 (New York City) +1-408-418-9388 US; Toll Access code: 2340 752 5250 Pre bid conference location -Pre-Bid Conference at Webex Link: https://nycacs.webex.com/nycacs/j.php?MTID=m94a02b17bd59edc8d6d1dc99bcf0e5e7 Meeting # 2343 375 8062 Mandatory: no Date/Time - 2023-12-12 14:00:00
3rd rowBid opening Location - Olmsted Center Annex, Flushing Meadows Corona Park, Flushing NY 11368 Meeting ID: 229 043 5542 Passcode: 763351
4th rowPre bid conference location -via Microsoft TEAMS Interested parties should contact authorized agency contact for link. Mandatory: no Date/Time - 2022-11-08 11:00:00 For the agency to evaluate the services and solution provided, it is in the City's interest to evaluate the proposer's quality of experience, demonstrated organizational capability and proposed approach and determine that the offered price is fair and reasonable.
5th rowPre bid conference location -https://us02web.zoom.us/j/2290435542?pwd=VFovbDl6UTVFNXl3ZGxPYUVsQU5kZz09 Meeting ID: 229 043 5542 Passcode: 763351 Mandatory: no Date/Time - 2023-11-22 10:30:00
ValueCountFrequency (%)
to 680
 
3.5%
bid 607
 
3.1%
the 537
 
2.8%
518
 
2.7%
conference 462
 
2.4%
in 452
 
2.3%
location 375
 
1.9%
ny 369
 
1.9%
link 329
 
1.7%
opening 301
 
1.6%
Other values (1556) 14773
76.1%
2023-12-09T21:26:05.044908image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19368
 
13.7%
e 10116
 
7.2%
o 8832
 
6.2%
n 7874
 
5.6%
i 7393
 
5.2%
t 7221
 
5.1%
r 5451
 
3.9%
a 5266
 
3.7%
s 4533
 
3.2%
c 4276
 
3.0%
Other values (78) 61058
43.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 86636
61.3%
Space Separator 19373
 
13.7%
Decimal Number 13234
 
9.4%
Uppercase Letter 13135
 
9.3%
Other Punctuation 5588
 
4.0%
Dash Punctuation 2002
 
1.4%
Control 521
 
0.4%
Close Punctuation 287
 
0.2%
Open Punctuation 286
 
0.2%
Math Symbol 251
 
0.2%
Other values (2) 75
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 10116
11.7%
o 8832
10.2%
n 7874
 
9.1%
i 7393
 
8.5%
t 7221
 
8.3%
r 5451
 
6.3%
a 5266
 
6.1%
s 4533
 
5.2%
c 4276
 
4.9%
l 3604
 
4.2%
Other values (16) 22070
25.5%
Uppercase Letter
ValueCountFrequency (%)
P 1214
 
9.2%
N 1045
 
8.0%
M 1038
 
7.9%
T 876
 
6.7%
S 852
 
6.5%
Y 794
 
6.0%
D 789
 
6.0%
O 664
 
5.1%
B 642
 
4.9%
C 584
 
4.4%
Other values (16) 4637
35.3%
Other Punctuation
ValueCountFrequency (%)
: 1474
26.4%
/ 1297
23.2%
. 1231
22.0%
, 910
16.3%
# 141
 
2.5%
' 136
 
2.4%
% 133
 
2.4%
? 125
 
2.2%
; 57
 
1.0%
@ 49
 
0.9%
Other values (3) 35
 
0.6%
Decimal Number
ValueCountFrequency (%)
0 2947
22.3%
1 2120
16.0%
2 2085
15.8%
3 1418
10.7%
4 912
 
6.9%
9 887
 
6.7%
5 844
 
6.4%
7 794
 
6.0%
6 670
 
5.1%
8 557
 
4.2%
Space Separator
ValueCountFrequency (%)
19368
> 99.9%
  5
 
< 0.1%
Control
ValueCountFrequency (%)
 519
99.6%
2
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 275
95.8%
] 12
 
4.2%
Open Punctuation
ValueCountFrequency (%)
( 274
95.8%
[ 12
 
4.2%
Math Symbol
ValueCountFrequency (%)
= 127
50.6%
+ 124
49.4%
Dash Punctuation
ValueCountFrequency (%)
- 2002
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 67
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 99771
70.6%
Common 41617
29.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 10116
 
10.1%
o 8832
 
8.9%
n 7874
 
7.9%
i 7393
 
7.4%
t 7221
 
7.2%
r 5451
 
5.5%
a 5266
 
5.3%
s 4533
 
4.5%
c 4276
 
4.3%
l 3604
 
3.6%
Other values (42) 35205
35.3%
Common
ValueCountFrequency (%)
19368
46.5%
0 2947
 
7.1%
1 2120
 
5.1%
2 2085
 
5.0%
- 2002
 
4.8%
: 1474
 
3.5%
3 1418
 
3.4%
/ 1297
 
3.1%
. 1231
 
3.0%
4 912
 
2.2%
Other values (26) 6763
 
16.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 141379
> 99.9%
None 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19368
 
13.7%
e 10116
 
7.2%
o 8832
 
6.2%
n 7874
 
5.6%
i 7393
 
5.2%
t 7221
 
5.1%
r 5451
 
3.9%
a 5266
 
3.7%
s 4533
 
3.2%
c 4276
 
3.0%
Other values (76) 61049
43.2%
None
ValueCountFrequency (%)
  5
55.6%
§ 4
44.4%

other_info_2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

other_info_3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

vendor_name
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

vendor_address
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

printout_1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

printout_2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

printout_3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

document_links
URL

MISSING 

Distinct194
Distinct (%)100.0%
Missing806
Missing (%)80.6%
Memory size115.8 KiB
https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230929110&amp;DocumentID=178090,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230929110&amp;DocumentID=178091,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230929110&amp;DocumentID=178092,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230929110&amp;DocumentID=178093,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230929110&amp;DocumentID=178094,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230929110&amp;DocumentID=178095
 
1
https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Current&amp;RequestID=20231026113&amp;DocumentID=178196
 
1
https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230427116&amp;DocumentID=177485
 
1
https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230831117&amp;DocumentID=177971,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230831117&amp;DocumentID=178136
 
1
https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Current&amp;RequestID=20231103101&amp;DocumentID=178269
 
1
Other values (189)
189 
(Missing)
806 
ValueCountFrequency (%)
https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230929110&amp;DocumentID=178090,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230929110&amp;DocumentID=178091,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230929110&amp;DocumentID=178092,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230929110&amp;DocumentID=178093,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230929110&amp;DocumentID=178094,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230929110&amp;DocumentID=178095 1
 
0.1%
https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Current&amp;RequestID=20231026113&amp;DocumentID=178196 1
 
0.1%
https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230427116&amp;DocumentID=177485 1
 
0.1%
https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230831117&amp;DocumentID=177971,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230831117&amp;DocumentID=178136 1
 
0.1%
https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Current&amp;RequestID=20231103101&amp;DocumentID=178269 1
 
0.1%
https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230712137&amp;DocumentID=177696,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230712137&amp;DocumentID=177780 1
 
0.1%
https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20221220110&amp;DocumentID=177036 1
 
0.1%
https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230126101&amp;DocumentID=176916,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230126101&amp;DocumentID=176917,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230126101&amp;DocumentID=176918 1
 
0.1%
https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230426113&amp;DocumentID=177402,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230426113&amp;DocumentID=177403,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230426113&amp;DocumentID=177500,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230426113&amp;DocumentID=177398,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230426113&amp;DocumentID=177399,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230426113&amp;DocumentID=177400,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230426113&amp;DocumentID=177401 1
 
0.1%
https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230717104&amp;DocumentID=177708 1
 
0.1%
Other values (184) 184
 
18.4%
(Missing) 806
80.6%
ValueCountFrequency (%)
https 194
 
19.4%
(Missing) 806
80.6%
ValueCountFrequency (%)
a856-cityrecord.nyc.gov 194
 
19.4%
(Missing) 806
80.6%
ValueCountFrequency (%)
/Search/GetFile 194
 
19.4%
(Missing) 806
80.6%
ValueCountFrequency (%)
SectionID=6&amp;RequestStatus=Current&amp;RequestID=20231003114&amp;DocumentID=178118 1
 
0.1%
SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230410103&amp;DocumentID=177383 1
 
0.1%
SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230130112&amp;DocumentID=176940 1
 
0.1%
SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230628101&amp;DocumentID=177629,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230628101&amp;DocumentID=177630,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230628101&amp;DocumentID=177631,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230628101&amp;DocumentID=177633,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230628101&amp;DocumentID=177634,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230628101&amp;DocumentID=177635,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230628101&amp;DocumentID=177638,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230628101&amp;DocumentID=177810,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230628101&amp;DocumentID=177811 1
 
0.1%
SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230901111&amp;DocumentID=177960,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230901111&amp;DocumentID=177999 1
 
0.1%
SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230908109&amp;DocumentID=177982 1
 
0.1%
SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230207128&amp;DocumentID=176950,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230207128&amp;DocumentID=176951,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230207128&amp;DocumentID=176952,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230207128&amp;DocumentID=176953 1
 
0.1%
SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230530126&amp;DocumentID=177704 1
 
0.1%
SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230425114&amp;DocumentID=177392 1
 
0.1%
SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230926109&amp;DocumentID=178096,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230926109&amp;DocumentID=178097,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230926109&amp;DocumentID=178098,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230926109&amp;DocumentID=178099,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230926109&amp;DocumentID=178100,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230926109&amp;DocumentID=178101,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230926109&amp;DocumentID=178185,https://a856-cityrecord.nyc.gov/Search/GetFile?SectionID=6&amp;RequestStatus=Archived&amp;RequestID=20230926109&amp;DocumentID=178194 1
 
0.1%
Other values (184) 184
 
18.4%
(Missing) 806
80.6%
ValueCountFrequency (%)
194
 
19.4%
(Missing) 806
80.6%

event_date
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

building_name
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

street_address_1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

street_address_2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

city
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

state
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

zip_code
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB